Existing systems for personality trait prediction from text does the prediction separately for different sources of data like social media, call detail records, email. There are systems available that discloses multiple ways of performing personality prediction from text. The detection of different personality from text has been used widely across multiple fields, for example, one of the main areas, hiring process wherein personality prediction from text is currently used for determining                Whether a personality is suitable for testing job, research manager, etc. . . . ?        Whether he/she a good team player?        
Personality prediction also helps to understand state of personality namely confused, organized, abstract or definitive. There are different techniques for predicting the personality from text. A person may typically have more than one personality trait but current systems are not able to identify which is the most prominent and less significant trait from the multiple personality traits identified.
The limitation of the current systems is how to correlate the information on the multiple personality traits that have been identified from the text from different sources of data. This limitation stems from the fact that the current systems do not go into deep levels like analysis of texts based on different topics and correlating them based on the prominent personality traits. Further, current systems do not know how to automate the above process in an efficient manner according to need and for benefit of different businesses.
Therefore, it would be desirable to have a system and a method for predicting the personality of the person by correlating the information obtained from different sources of data. Further, it would be desirable to have a mechanism for learning from user response to the predicted personality